About the Team

The Data Engineering team exists from almost the beginning of the company, even before the data (!). It gives you an idea of how important the data is at Resilience. The team is currently composed of one lead and one engineer but we need extra hands. As part of the crew you will have the opportunity to collaborate with many different teams across R&D (Product, Data Science…) but not only (Operational, Medical…).

Missions

As a data engineer at Resilience you will have the opportunity to have an impact on the whole platform, collecting, structuring and processing the data used by all of our products and services. If you care about data, their privacy, and enjoy defining and implementing the most-suited technical architecture to answer product challenges you are in the right place! Please find more details about the missions below.

Data Engineering Factory

• Design the most appropriate architecture to build the health-related data factory
• Collaborate with the internal Resilience teams (Medical, R&D, Ops etc.) to understand and define the best way to structure the data
• Develop and maintain jobs or services in charge of ingesting, cleaning, processing and storing the data in our internal data warehouse
• Develop and maintain services to make the data available to the whole Resilience platform/teams and ensure privacy and security concerns are well handled

Data Platform Tooling

• Explore, develop and deploy tools to facilitate the data team(s) (Data Engineering + Data Science) daily work
• Implement and maintain tools to improve data observability, traceability and quality at the company level

Hard-skills

• Be familiar with at least one Object-Oriented Programming language (Python, JVM-based…) [must-have]
• Strong SQL modelization (normal forms, star schema…) and analytics (SQL-based) skills [must-have]
• NoSQL DB knowledge [optional]

Experiences

• Structure complex data according to business constraints [must-have]
• Design, implement and maintain data ingestion and processing pipelines in production systems [must-have]
• Contribute to Services Oriented Architecture and familiar with Domain Driven Development [must-have]
• Implement and maintain messaged-based architecture (Kafka) [nice-to-have]
• Tests and automations awareness [nice-to-have]
• Have some skills in data visualization [nice-to-have]
• Maintain architecture relying on workflow schedulers (Prefect, Airflow…) [optional]
• Deploy and maintain data platform tools (data catalog, lineage…) [optional]

Soft-skills

• Good communicator and able to adapt your speech according to the audience [must-have]
• Have interest for health ecosystem [must-have]
• Strong team player and ease collaboration with business teams [must-have]

• Interview with Data Engineer Lead [Assess the technical level and fit with Data Eng team]
• Technical coding test [Assess the technical basics]
• Technical design test [Assess the technical seniority]
• Interview with Product [Assess the collaboration and communication skills]
• Interview with Head of Data & CTO [Assess the technical level and fit with R&D]
• Interview with HR [Assess the fit with Resilience environment and start-up ecosystem]